architecture:
    backbone_dtype: float32
    force_embedding_gradients: false
    gradient_checkpointing: false
    intermediate_dropout: 0.0
    pretrained: true
    pretrained_weights: ''
augmentation:
    random_parent_probability: 0.0
    skip_parent_probability: 0.0
    token_mask_probability: 0.0
dataset:
    add_eos_token_to_answer: true
    add_eos_token_to_prompt: true
    add_eos_token_to_system: true
    answer_column: output
    chatbot_author: H2O.ai
    chatbot_name: h2oGPT
    data_sample: 0.01
    data_sample_choice:
    - Train
    - Validation
    limit_chained_samples: false
    mask_prompt_labels: true
    parent_id_column: None
    personalize: false
    prompt_column:
    - instruction
    system_column: None
    text_answer_separator: ''
    text_prompt_start: ''
    text_system_start: ''
    train_dataframe: /tmp/train_full.pq
    validation_dataframe: None
    validation_size: 0.01
    validation_strategy: automatic
environment:
    compile_model: false
    find_unused_parameters: false
    gpus:
    - ''
    huggingface_branch: main
    mixed_precision: false
    number_of_workers: 8
    seed: -1
    trust_remote_code: true
experiment_name: test-sequence-to-sequence-modeling-oasst
llm_backbone: t5-small
logging:
    logger: None
    neptune_project: test_org/test_project
output_directory: /tmp/output
prediction:
    batch_size_inference: 0
    do_sample: false
    max_length_inference: 16
    mmax_time: 0.0
    metric: Perplexity
    metric_gpt_model: gpt-3.5-turbo-0301
    metric_gpt_template: general
    min_length_inference: 2
    num_beams: 1
    num_history: 4
    repetition_penalty: 1.2
    stop_tokens: ''
    temperature: 0.3
    top_k: 0
    top_p: 1.0
problem_type: text_sequence_to_sequence_modeling
tokenizer:
    add_prompt_answer_tokens: false
    max_length: 32
    max_length_answer: 16
    max_length_prompt: 16
    padding_quantile: 1.0
training:
    batch_size: 2
    differential_learning_rate: 1.0e-05
    differential_learning_rate_layers: []
    drop_last_batch: true
    epochs: 1
    evaluate_before_training: false
    evaluation_epochs: 1.0
    grad_accumulation: 1
    gradient_clip: 0.0
    learning_rate: 0.0001
    lora: true
    use_dora: false
    lora_alpha: 16
    lora_dropout: 0.05
    lora_r: 4
    lora_target_modules: ''
    loss_function: TokenAveragedCrossEntropy
    optimizer: AdamW
    save_checkpoint: "last"
    schedule: Cosine
    train_validation_data: false
    warmup_epochs: 0.0
    weight_decay: 0.0
